package com.atguigu.day10;

import com.atguigu.bean.WaterSensor;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.annotation.DataTypeHint;
import org.apache.flink.table.annotation.FunctionHint;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.functions.AggregateFunction;
import org.apache.flink.table.functions.TableFunction;
import org.apache.flink.types.Row;

import static org.apache.flink.table.api.Expressions.$;
import static org.apache.flink.table.api.Expressions.call;

public class Flink05_UDF_AggFun {
    public static void main(String[] args) {
        //1.获取流的执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);

        //2.读取元素得到DataStream
//        DataStreamSource<WaterSensor> waterSensorDataStreamSource = env.fromElements(new WaterSensor("sensor_1", 1000L, 10),
//                new WaterSensor("sensor_1", 2000L, 20),
//                new WaterSensor("sensor_2", 3000L, 30),
//                new WaterSensor("sensor_1", 4000L, 40),
//                new WaterSensor("sensor_1", 5000L, 50),
//                new WaterSensor("sensor_2", 6000L, 60));

        SingleOutputStreamOperator<WaterSensor> waterSensorDataStreamSource = env.socketTextStream("localhost", 9999)
                .map(new MapFunction<String, WaterSensor>() {
                    @Override
                    public WaterSensor map(String value) throws Exception {
                        String[] split = value.split(",");
                        return new WaterSensor(split[0], Long.parseLong(split[1]), Integer.parseInt(split[2]));
                    }
                });

        //3.获取表的执行环境
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        //4.将流转为表
        Table table = tableEnv.fromDataStream(waterSensorDataStreamSource);

        //不注册直接使用
      /*  table
                .groupBy($("id"))
                .select($("id"),call(MyUDAF.class, $("vc")))
                .execute().print();
*/

        //先注册再使用
        tableEnv.createTemporarySystemFunction("MyAvg", MyUDAF.class);

    /*    table
                .groupBy($("id"))
                .select($("id"),call("MyAvg", $("vc")))
                .execute().print();*/

        //sql
        tableEnv.executeSql("select " +
                "id," +
                "MyAvg(vc) " +
                "from "+table+
                " group by id").print();


    }
    //自定义一个聚合函数，多进一出，根据id求vc平均值
    public static class MyAcc{
        public Integer vcCount;
        public Integer vcSum;
    }
    public static class MyUDAF extends AggregateFunction<Double,MyAcc>{

        @Override
        public MyAcc createAccumulator() {
            MyAcc myAcc = new MyAcc();
            myAcc.vcCount = 0;
            myAcc.vcSum = 0;
            return myAcc;
        }

        public void accumulate(MyAcc acc,Integer value){
            acc.vcSum += value;
            acc.vcCount += 1;
        }
        @Override
        public Double getValue(MyAcc accumulator) {
            return accumulator.vcSum*1D/accumulator.vcCount;
        }
    }

}
